• Fashion & Textile Research Journal
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• v.14 no.1
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• pp.64-74
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• 2012

The purpose of this study was to find purchase appraisal standard and post-purchase satisfaction for natural dyeing products. The data used for this study were collected from the women in their from 20's to 50's who are living in the regions of Busan, Ulsan, and Gyeongnam in Korea. The questionnaire of 537 copies was used for a statistical analysis. To analyze data, 2-test, t-test, Cronbach's a test, factor analysis, ANOVA, Duncan test, regression analysis, etc. were carried out. A used statistical package was SPSS 14.0. The analysis results were as follows. The purchase appraisal standards for natural dyeing products were identified as practicality and reliability, suitability of use, symbolic property of status, design property, and convenience of buying. As the analysis result for purchase appraisal standard according to the demographic characteristics, the purchase appraisal standard according to most demographic characteristics showed significant difference. The factors of post-purchase satisfaction for natural dyeing products were verified as product modification and durability, design and price, hygienic property and product quality. As the analysis results of post-purchase satisfaction for natural dyeing products according to demographic characteristics, the post-purchase satisfaction according to demographic characteristics showed significant difference. The factors affecting post-purchase satisfaction were verified as product quality, kinds of item, color change, product lifespan, color change, etc. Consequently, because the purchase appraisal standard of natural dyeing product is very various, it is necessary to enhance post-purchase satisfaction of natural dyeing products by reflecting these factors in advance at the product development stage.

• Journal of Fashion Business
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• v.15 no.1
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• pp.50-62
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• 2011

The purpose of this study is to catch the difference for the appraisal standard of a product which the adult women's consumers think importantly when they purchase the clothing made of organic cotton and the appraisal standard according to the demographic characteristics. The data collection for research was done for the women in from their 20's to 50's who are living in the regions of Gyungnam, Busan, Ulsan in Korea. The copies of the used questionnaire were 622 copies. To analyze the collected data, ${\chi}^2$-test, t-test, Cronbach's ${\alpha}$ test, ANOVA, Duncan test were carried out by SPSS 14.0. As the analysis result of data, the appraisal standard for purchasing the clothing made of organic cotton was classified with the five factors. The appraisal standard which the adult women's consumers think importantly when they purchase the clothing made of organic cotton showed the significant difference according to the demographic characteristics. The ratio for post-purchase dissatisfaction showed higher than the one for satisfaction. The dissatisfaction showed the significant difference according to the demographic characteristics. The dissatisfaction for a high price, color and insufficient design showed a relatively high ratio.

• The Korean Journal of Food And Nutrition
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• v.20 no.2
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• pp.226-239
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• 2007

The purpose of this study was to identify the problems related to the purchasing processes of school foodservices that should be corrected for the food service safety, by examining the purchasing processes and the status of supplier selection. A questionnaire was given to 300 dietitians working at self-operated food services. Ninety-eight responses, excluding incomplete answers, were used for the statistical analysis. The survey consisted of three parts: the general characteristics of the school foodservice and dietitian, purchasing processes and supplier selection, and the purchase specifications. We found that 84% of the contract was made by informal purchasing, and the contract period was 6 months or one year. For supplier selection, problems related to the document screening systems were the superficiality of the content(45.7%) and the absence or lack of clarity of the appraisal criteria(34.8%). The important factors for the facility and equipment standards of suppliers were included unclear evaluation methods for content(41.1%) and inappropriate appraisal lists(21.1%), while unclear evaluation methods for content(41.9%) and absence or lack of clarity of the appraisal criteria(20.4%) were the problems pertaining to the supplier evaluation checklist. When using the Food Labeling Standards to select suppliers, confirmation of the sell-by date and the storage method had the highest score at 3.85 out of 5. For supplier selection, only 25% of the contract was made by using the purchase specifications. The levels of satisfaction of with Kimchi and rice cakes suppliers were significantly different according to employment type and educational background, respectively. Depending on working experiences, satisfaction was significantly different for the use of document screening, as a standard for the selection and management of suppliers, and for the facility and equipment standards of suppliers, The use of purchase specifications was different by employment type, while the use of purchase specifications for contracts was different by working experience. These results imply that the specialization of suppliers is necessary to unsure food safety. Therefore, the objective methods to evaluate the suppliers should be developed by the government, and appropriate education programs for dietitians should be prepared to enhance the utilization of purchase specifications.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.233-265
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• 1996

We examine the impact of public and private information on price movements using the thirty DJIA stocks and twenty-one NASDAQ stocks. We find that the standard deviation of daily returns on information days (dividend announcement, earnings announcement, insider purchase, or insider sale) is much higher than on no-information days. Both public information matters at the NYSE, probably due to masked identification of insiders. Earnings announcement has the greatest impact for both DJIA and NASDAQ stocks, and there is some evidence of positive impact of insider asle on return volatility of NASDAQ stocks. There has been considerable debate, e.g., French and Roll (1986), over whether market volatility is due to public information or private information-the latter gathered through costly search and only revealed through trading. Public information is composed of (1) marketwide public information such as regularly scheduled federal economic announcements (e.g., employment, GNP, leading indicators) and (2) company-specific public information such as dividend and earnings announcements. Policy makers and corporate insiders have a better access to marketwide private information (e.g., a new monetary policy decision made in the Federal Reserve Board meeting) and company-specific private information, respectively, compated to the general public. Ederington and Lee (1993) show that marketwide public information accounts for most of the observed volatility patterns in interest rate and foreign exchange futures markets. Company-specific public information is explored by Patell and Wolfson (1984) and Jennings and Starks (1985). They show that dividend and earnings announcements induce higher than normal volatility in equity prices. Kyle (1985), Admati and Pfleiderer (1988), Barclay, Litzenberger and Warner (1990), Foster and Viswanathan (1990), Back (1992), and Barclay and Warner (1993) show that the private information help by informed traders and revealed through trading influences market volatility. Cornell and Sirri (1992)' and Meulbroek (1992) investigate the actual insider trading activities in a tender offer case and the prosecuted illegal trading cased, respectively. This paper examines the aggregate and individual impact of marketwide information, company-specific public information, and company-specific private information on equity prices. Specifically, we use the thirty common stocks in the Dow Jones Industrial Average (DJIA) and twenty one National Association of Securities Dealers Automated Quotations (NASDAQ) common stocks to examine how their prices react to information. Marketwide information (public and private) is estimated by the movement in the Standard and Poors (S & P) 500 Index price for the DJIA stocks and the movement in the NASDAQ Composite Index price for the NASDAQ stocks. Divedend and earnings announcements are used as a subset of company-specific public information. The trading activity of corporate insiders (major corporate officers, members of the board of directors, and owners of at least 10 percent of any equity class) with an access to private information can be cannot legally trade on private information. Therefore, most insider transactions are not necessarily based on private information. Nevertheless, we hypothesize that market participants observe how insiders trade in order to infer any information that they cannot possess because insiders tend to buy (sell) when they have good (bad) information about their company. For example, Damodaran and Liu (1993) show that insiders of real estate investment trusts buy (sell) after they receive favorable (unfavorable) appraisal news before the information in these appraisals is released to the public. Price discovery in a competitive multiple-dealership market (NASDAQ) would be different from that in a monopolistic specialist system (NYSE). Consequently, we hypothesize that NASDAQ stocks are affected more by private information (or more precisely, insider trading) than the DJIA stocks. In the next section, we describe our choices of the fifty-one stocks and the public and private information set. We also discuss institutional differences between the NYSE and the NASDAQ market. In Section II, we examine the implications of public and private information for the volatility of daily returns of each stock. In Section III, we turn to the question of the relative importance of individual elements of our information set. Further analysis of the five DJIA stocks and the four NASDAQ stocks that are most sensitive to earnings announcements is given in Section IV, and our results are summarized in Section V.